Our PhD and MS level biostatisticians are highly trained in a range of statistical and analytic methods, including:
- Longitudinal data analysis
- ANOVA, regression, logistic regression
- Bayesian data analyses
- Sample size and power estimation
- Statistical genomics
- Survival analyses
- Principal component and factor analysis
- Path modeling
- Structural equation modeling
- Cluster analysis
- Complex survey data analysis
- Statistical simulations and graphics
- Profile analysis
- Gene expression data analysis
- Mixed effects models
- Generalized Estimating Equations (GEE)
- Propensity Score Matching (PSM)
- Evaluation of medical tests for classification and prediction
- Estimation of median lethal doses (LD50)/quantal dose-response curves
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Biostatisticians & Epidemiologists
Vikki G. Nolan, DSc, MPH Assistant Professor of Epidemiology, University of Memphis She received her MPH from Yale University and her doctoral degree from Boston University School of Public Health. Dr. Nolan’s primary research interests are sickle cell disease, a field she worked in for six years while at Boston University, and cancer epidemiology, which she specialized in while employed at St. Jude Children’s Research Hospital prior to joining the University of Memphis faculty. In addition to her primary research interests, she is interested in and has participated in research around genetics, physical fitness, aging, community health, and infectious diseases.
Xinhua Yu, MD, PhD Associate Professor of Epidemiology, University of Memphis Xinhua Yu, MD, PhD, MStat, is an Assistant Professor of Epidemiology at the School of Public Health, University of Memphis. He earned a medical degree in preventive medicine from Shanghai Medical University (now College of Medicine at Fudan University) in Shanghai, China, and a PhD in epidemiology and MStat in statistics from the University of Minnesota at Twin Cities campus. Dr. Yu has extensive experience in cardiovascular disease epidemiology, obesity, and physical activity. His recent research interest is clinical epidemiology, especially cancer epidemiology.